Free-living movement (physical activity [PA] and sedentary behavior [SB]) and eating behaviors (energy intake [EI] and food choice) affect energy balance and therefore have the potential to influence weight loss (WL). This study explored whether free-living movement and/or eating behaviors measured early (week 3) in a 14-week WL programme or their change during the intervention are associated with WL in women. In the study, 80 women ( ± age: 42.0 ± 12.4 years) with overweight or obesity [body mass index (BMI): 34.08 ± 3.62 kg/m] completed a 14 week WL program focused primarily on diet (commercial or self-led). Body mass (BM) was measured at baseline, and again during week 2 and 14 along with body composition. Free-living movement (SenseWear Armband) and eating behavior (weighed food diaries) were measured for 1 week during week 3 and 12. Hierarchical multiple regression analyses examined whether early and early-late change in free-living movement and eating behavior were associated with WL. The differences in behavior between clinically significant weight losers (CWL; ≥5% WL) and non-clinically significant weight losers (NWL; ≤ 3% WL) were compared. The energy density of food consumed [β = 0.45, < 0.001] and vigorous PA [β = -0.30, < 0.001] early in the intervention (regression model 1) and early-late change in light PA [β = -0.81 < 0.001], moderate PA [β = -1.17 < 0.001], vigorous PA [β = -0.49, < 0.001], total energy expenditure (EE) [β = 1.84, < 0.001], and energy density of food consumed [β = 0.27, = 0.01] (regression model 2) significantly predicted percentage change in BM. Early in the intervention, CWL consumed less energy dense foods than NWL [ = 0.03]. CWL showed a small but significant increase in vigorous PA, whereas NWL showed a slight decrease in PA [ = 0.04]. Both early and early-late change in free-living movement and eating behaviors during a 14 week WL program are predictors of WL. These findings demonstrate that specific behaviors that contribute to greater EE (e.g., vigorous PA) and lower EI (e.g., less energy-dense foods) are related to greater WL outcomes. Interventions targeting these behaviors can be expected to increase the effectiveness of WL programs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8478016 | PMC |
http://dx.doi.org/10.3389/fnut.2021.688295 | DOI Listing |
JMIR Form Res
December 2024
Department of Sports Science, College of Education, Zhejiang University, No. 866, Yuhangtang Road, Hangzhou, 310030, China, 86 18667127699.
Background: Smartwatches are increasingly popular for physical activity and health promotion. However, ongoing validation studies on commercial smartwatches are still needed to ensure their accuracy in assessing daily activity levels, which is important for both promoting activity-related health behaviors and serving research purposes.
Objective: This study aimed to evaluate the accuracy of a popular smartwatch, the Huawei Watch GT2, in measuring step count (SC), total daily activity energy expenditure (TDAEE), and total sleep time (TST) during daily activities among Chinese adults, and test whether there are population differences.
J Neuroeng Rehabil
December 2024
Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Boston, MA, USA.
Background: Wearable technology offers objective and remote quantification of disease progression in neurological diseases such as amyotrophic lateral sclerosis (ALS). Large population studies are needed to determine generalization and reproducibility of findings from pilot studies.
Methods: A large cohort of patients with ALS (N = 202) wore wearable accelerometers on their dominant and non-dominant wrists for a week every two to four weeks and self-entered the ALS Functional Rating Scale-Revised (ALSFRS-RSE) in similar time intervals.
Int J Behav Nutr Phys Act
December 2024
Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Background: It remains unclear what lifestyle behaviors are optimal for controlling postprandial glucose responses under real-world circumstances in persons without diabetes. We aimed to assess associations of diet, physical activity, and sleep with postprandial glucose responses in Asian adults without diabetes under free-living conditions.
Methods: We conducted an observational study collecting intensive longitudinal data using smartphone-based ecological momentary assessments, accelerometers, and continuous glucose monitors over nine free-living days in Singaporean men and women aged 21-69 years without diabetes.
J Med Internet Res
December 2024
Alliance for Research in Exercise, Nutrition and Activity, Allied Health and Human Performance, University of South Australia, Adelaide, Australia.
Background: With 1 in 3 adults globally living with chronic conditions and the rise in smartphone ownership, mobile health apps have become a prominent tool for managing lifestyle-related health behaviors and mental health. However, high rates of app abandonment pose challenges to their effectiveness.
Objective: We explored the abandonment of apps used for managing physical activity, diet, alcohol, smoking, and mental health in free-living conditions, examining the duration of app use before abandonment and the underlying reasons.
Sensors (Basel)
November 2024
Haute-Ecole Arc Santé, HES-SO University of Applied Sciences and Arts Western Switzerland, 2000 Neuchâtel, Switzerland.
The attractor complexity index (ACI) is a recently developed gait analysis tool based on nonlinear dynamics. This study assesses ACI's sensitivity to attentional demands in gait control and its potential for characterizing age-related changes in gait patterns. Furthermore, we compare ACI with classical gait metrics to determine its efficacy relative to established methods.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!